Visualization of dynamic connectivity in high electrode-density EEG
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A visualization methodology for the analysis of dynamic synchronization in electroencephalograph^ signals is presented here. The proposed method is based on a seeded region-growing segmentation of the time-frequency space in terms of spatial connectivity patterns, a process that can be fully automated by cleverly choosing the seeds. A Bayesian regularization technique is applied to further improve the results. Finally, preliminary results from the analysis of a high electrode-density dataset with 120 channels are shown. © Springer-Verlag Berlin Heidelberg 2008.
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Bayesian regularization; Connectivity pattern; Data sets; Electroencephalograph signals; Seeded region; Time-frequency space; Computer science; Electroencephalography; Visualization; Dynamic analysis
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